Font recognition was poor, due to forcing a 1st and 2nd choice at
a character level, when the total score for the correct font is often
correct at the word level, so allowed the propagation of a full set
of fonts and scores to the word recognizer, which can now decide word
level fonts using the scores instead of simple votes.
Change precipitated a cleanup of output data structures for classifier
results, eliminating ScoredClass and INT_RESULT_STRUCT, with a few
extra elements going in UnicharRating, and using that wherever possible.
That added the extra complexity of 1-rating due to a flip between 0 is
good and 0 is bad for the internal classifier scores before they are
converted to rating and certainty.
Eliminated the flexfx scheme for calling global feature extractor functions
through an array of function pointers.
Deleted dead code I found as a by-product.
This CL does not change BlobToTrainingSample or ExtractFeatures to be full
members of Classify (the eventual goal) as that would make it even bigger,
since there are a lot of callers to these functions.
When ExtractFeatures and BlobToTrainingSample are members of Classify they
will be able to access control parameters in Classify, which will greatly
simplify developing variations to the feature extraction process.
